Predictive system for context-aware custom web presentation

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Web application is critical for the growth of a company's business. It is a significant platform for information sharing with existing and potential customers and an important online marketing tool. The project employs machine intelligence techniques and tools to customize web page presentation to the web-site visitors, which will significantly reduce their search time and frustration. The time a visitor spends on searching for relevant content is critical for both the visitors and the web site owners. The search time grows rapidly as the web content increases, which causes frustration to the visitors and drops their Quality of Experience (QoE). The frustration drives away customers from potential business opportunity to the web site owners. Hence, building intelligence in web presentation logic to present customized content to users within real time is critical for retaining customers by improving their surfing experience. In this project, we aim to build a predictive system for context-aware processing of user requests to implement customized presentation logic. The proposed customized web presentation system includes context profile for processing web requests and predictive algorithms based on machine learning and recommender system to identify the custom content. It will be implemented and integrated with innohub platform. It will enable innohub to offer business growth to its clients by improving the QoE of visitors to their web sites. Further, it will not only contribute to increase R&D in Canada but also to its economy by driving more customers into the revenue stream.